Senior Supply Chain Solutions Analyst

ZENITH INFOTEK LLC; San Jose (CA); Hybrid; USD 150,000 - 190,000; Full time

Job summary

Meta is seeking a Senior Supply Chain Solutions Analyst in Sunnyvale, CA (Hybrid, 3 days a week) to build internal tools and deliver data-driven analyses that power our supply chain risk intelligence program. You will embed with the Strategic Sourcing team, turning messy BOMs, MPNs, and supplier data into clean, validated datasets and practical tools used by sourcing managers.

You will validate data, cross-reference external sources, and develop automated QA checks, dashboards, and AI-assisted

Qualifications

• 5+ years as technical analyst, solutions engineer, or applied data science role.
• Strong Python scripting and data manipulation with pandas.
• Proficient SQL for large datasets and complex joins.
• Experience connecting to external APIs and data sources.
• Ability to deliver working internal tools quickly.

Responsibilities

• Validate and cleanse internal BOM and MPN data across systems.
• Cross-reference supplier data with external sources to identify gaps and risks.
• Build automated data quality checks and exception workflows.
• Deliver ad-hoc analyses on lifecycle risk and single-sourcing parts.

Skills

Python

SQL

APIs

Data analysis

Data wrangling

Education

Bachelor's degree in a technical field

Tools

Flask/Streamlit/React

Job description

Role: Senior Supply Chain Solutions Analyst

Location: Sunnyvale, CA (Hybrid, 3 days a week)

Role Summary

We're looking for a senior solutions analyst to build internal tools and deliver data-driven analyses that power Meta's supply chain risk intelligence program. Think "forward-deployed engineer", you'll sit embedded with the Strategic Sourcing team, understand their problems firsthand, and build the last-mile applications and analyses they actually use. This isn't a platform or infrastructure role. Your job is to take messy real-world supply chain data - BOMs, supplier records, component lifecycle information - and turn it into clean, validated datasets and working internal tools that help sourcing managers make faster, better decisions.

What You'll Do

• Validate and cleanse internal BOM (Bill of Materials) and MPN (Manufacturer Part Number) data across systems
• Cross-reference supplier data against external sources (Z2Data, DigiKey, SiliconExpert) to identify gaps, risks, and inconsistencies
• Build automated data quality checks and exception workflows
• Deliver ad-hoc analyses, e.g., "which components in this program have lifecycle risk?" or "where are we single-sourced on long-lead parts?"

Internal Tools & Applications

• Build and iterate on custom internal tools for supply chain risk monitoring (Python, web-based dashboards, APIs)
• Integrate external market intelligence platforms into internal workflows
• Develop AI-assisted features - risk scoring, lifecycle classification, early warning signals
• Create self-service analytics and visualizations for non-technical sourcing leads

Solution Design

• Translate supply chain business problems into technical solutions
• Prototype fast - get a working tool in front of users within days, not months
• Work with existing data infrastructure (pipelines, tables, etc) rather than building from scratch
• Identify opportunities to automate manual processes with AI/LLM tools

Required Skills

• 5+ years in a technical analyst, solutions engineer, or applied data science role
• Strong Python - scripting, data manipulation (pandas), API integrations, light web development
• Proficient in SQL — can query large datasets, write complex joins, work with partitioned tables
• Experience connecting to and working with external APIs and data sources
• Ability to build working internal tools quickly - web apps, dashboards, notebooks, scripts
• Comfortable working with messy, real-world data - reconciling across sources, handling edge cases
• Strong communication — can present findings to non-technical stakeholders clearly

Nice to Have

• Supply chain, procurement, or hardware operations background
• Familiarity with electronic component data (BOMs, AVLs, MPNs, lifecycle stages)
• Experience with component databases (DigiKey, Octopart, Z2Data, SiliconExpert)
• Comfort with AI/ML tools - LLMs, classification models, or using AI assistants to accelerate work
• Web frameworks (Flask, Streamlit, React) for rapid prototyping
• Meta internal tools (Bento, Presto/Hive, Unidash, Dataswarm) or equivalent at scale

Working Style

• Embedded with the sourcing team, you understand the business problem before you write code
• Ship fast, iterate often - working tools in days, polished in weeks
• High autonomy - own your solutions end-to-end
• Collaborative — work closely with the XFN team, Supply Chain Transformation data engineers, and sourcing pillar leads
• Comfortable with ambiguity, half the value is figuring out what to build

Flexible work from home options available.